Ecological Civilization in Practice: An Exploratory Study of Urban Agriculture in Four Chinese Cities
Bibliographic record
Abstract
Chinese development priorities have, since 2012, been formally framed under the slogan “Ecological Civilization” (EC). Simultaneously, urban agriculture (UA) has emerged as a potential strategy to contribute to urban food security in China, in wake of the COVID-19 pandemic. In this paper, we interrogate EC as an approach to urban and agricultural development in China and explore how EC manifests in practical terms, through a case study of urban agriculture. Over four months, we conducted on-site interviews and surveys with UA practitioners in four Chinese cities to understand how their experiences are negotiated with the state, in the context of EC. We find through our case study that capital-intensive and peri-urban approaches to UA are favoured in the context of EC, while small-scale intra-urban initiatives are actively discouraged in policy but passively accepted in practice and enforcement. This is despite all forms of UA promoting key goals for EC, including beautifying urban areas, increasing the quality of life for urban residents, and reconnecting individuals with food growing culture. Despite novel developments in innovative agricultural practices in both rural and urban contexts, the EC pathway risks overlooking grassroots initiatives and meeting local residents’ needs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".